Colour Science for Python
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Updated
Jun 21, 2024 - Python
Colour Science for Python
Generate harmonious colors freely.
Curated list of awesome colour science resources 😎
Colour science datasets for use with Colour
Image analysis tools based on Colour and Vispy
TensorFlow module for RGB (from / to) LAB color-space conversion.
WebGPU-based visuals for colour science applications
Pigment based painting analysis and editing
Colour - Maya
Various resources for Mitsuba 3
Colour - Spectroscope
Various resources for Eclat Digital - Ocean Light Simulator
Various colour science Dash apps built on top of Colour
The author's officially PyTorch Channel-Fusion implementation.
Colour - Branding
Developing a suitable way for applying histogram equalization for Color Images using RGB to HSI and RGB to YCbCr color space conversation. Comparing histogram equalized images using SNR/PSNR measures.
K-means clustering is an algorithm that groups similar data points into a predetermined number of clusters by minimizing the sum of squared distances between data points and their cluster centroids.
This model is based on BlazePose model developed by Google research. But the model uses Lab color space instead of RGB used originally in BlazePose
Various "webhook" resources for use with https://www.colour-science.org.
This script take two colour ranges from user through track bars and then detects the shared edge between the two if any in the input image.
Add a description, image, and links to the color-space topic page so that developers can more easily learn about it.
To associate your repository with the color-space topic, visit your repo's landing page and select "manage topics."